You know that sinking feeling when you realize your project data is
locked in someone else's cloud, and your compliance team is breathing
down your neck?
I've been there. After 30 years of consulting on engineering
transformations, I've watched teams go through the same cycle: adopt a
cloud-first PM tool, hit a security audit, scramble to find a
self-hosted alternative, and then discover that "self-hosted" often
means "watered-down features behind an enterprise sales call."
With Atlassian's Data Center end-of-life deadline now set for March
28, 2029, I'm getting calls weekly from teams who need a migration
path that doesn't force them into the cloud. They want AI project
tracking they can host themselves — not because cloud is bad, but
because their data, their workflows, and their regulatory requirements
are non-negotiable.
So I tested seven self-hosted platforms against a real scenario: a
cross-functional product launch with five team members, two-week
sprints, and a hard requirement that all data stays on-premise. Here's
what I found.
Before diving into the tools, here's my evaluation framework — so you
can judge whether my priorities match yours:
Here's the shortlist I landed on after narrowing down from about
twenty candidates:
** ONES.com** — Best for Jira DC migration with native AI
** Jira Software (Data** — Best for large
** GitLab Ultimate** — Best for DevSecOps teams
** Redmine with AI Plugins** — Best for
** Taiga.io** — Best for agile purists wanting clean UX
** Leantime** — Best for strategy-led small teams
** Wekan** — Best for kanban-only teams
I'll start with ONES.com because it's the one I keep recommending to
Jira Data Center refugees, and I want to explain why.
ONES.com is a unified platform — project management and knowledge base
in one. ONES Project handles
sprint planning, issue tracking, and workflow automation. ONES Wiki
covers documentation. Both are sold separately, and the free plan
supports up to 30 seats.
What stood out to me is their commitment to feature parity across
cloud, on-premise, and private cloud. You get the same AI capabilities
whether your servers sit in a locked cage or a public data center.
That's rare. Most vendors I've evaluated treat on-prem as a
second-class citizen.
For teams migrating from Jira Data Center, ONES supports Jira-compatible workflows, custom fields, and automation natively.
Your existing process logic maps over without a complete redesign. I
watched a client migrate two years of Jira history in under a week —
configuration, not re-engineering.
The AI features are native, not Marketplace plugins. Sprint analytics
surface bottlenecks automatically. AI-assisted tracking flags scope
creep before it becomes a problem. No stitching together three vendors
for features that should be built in. Where it falls short: The ecosystem is smaller than Atlassian's.
If your team depends on niche Marketplace apps, you'll need to check compatibility. And while the interface is clean, it doesn't have the
decades of UX polish that Jira has accumulated.
Pricing: Free plan covers 30 seats. Paid tiers scale from there.
For a 500-person team comparing against Jira Data Center (~$42K/year base + apps), ONES typically comes in significantly lower.
Jira Data Center is still the reference point everyone compares
against. Mature agile boards, massive Marketplace ecosystem, familiar
interface that most developers already know. But here's the reality I keep telling clients: Atlassian has announced
Data Center end-of-life for March 28, 2029. After that, your licenses
expire and the instance becomes read-only. That's not a rumor — it's a
hard deadline.
If you're already running Data Center and have years of investment in Marketplace apps, the smart move is to plan your migration now, not in
The AI capabilities are fragmented across Marketplace apps. I've seen
teams run 30+ plugins just to get reporting, planning, and automation
that feels modern. Annual costs with apps can approach double the base
license, and you're still managing servers yourself.
GitLab Ultimate is the natural choice if your definition of "project
tracking" is inseparable from the code itself — issues linked to
commits, epics tied to merge requests, value stream analytics derived
from deployment frequency. The AI capabilities in Ultimate are genuinely embedded, not bolt-on.
Merge request summaries explain what changed and why. Vulnerability
explanations translate security findings into plain language. Value
stream analytics show you exactly where work slows down.
The single-application architecture is a real advantage — one data
store, one auth layer, one upgrade cycle instead of stitching together
Jira + Bitbucket + Jenkins + SonarQube.
Where it falls short: It's developer-first, PM-second. If you have
non-technical stakeholders who need a friendly interface for roadmap
planning or sprint review, GitLab feels like an engineering tool
because it is one. And Ultimate pricing is not cheap.
Redmine is fully open-source, infinitely customizable, and completely
free. If you have in-house Ruby expertise and want maximum control,
nothing beats it on flexibility.
But "with AI plugins" is doing a lot of heavy lifting. You're
assembling your own AI stack from community plugins of varying quality
and maintenance. I spent a weekend getting a basic AI sprint summary
working — it required a separate LLM API key, custom configuration,
and broke on the first Redmine update.
Best for: Teams with dedicated engineering bandwidth who view PM
tooling as a platform to build on, not a product to consume.
Taiga.io gives you scrum and kanban with multi-project epics in a
clean, fast interface. Self-hosted via Docker, free, and the UX is
genuinely pleasant for agile purists.
But there's no meaningful AI capability. If your team specifically
wants AI-assisted tracking — the whole point of this evaluation —
Taiga doesn't deliver. It's a solid choice if you just want
self-hosted agile boards without the AI layer.
Leantime surprised me. It's designed for small to mid-size teams that
blend project management with strategic goal tracking. The AI task
generation from natural language input actually works — type "set up a
beta launch plan" and it generates a structured task list.
The strategy cascading is thoughtful: goals feed into milestones,
milestones feed into sprints. If your team struggles with the "why are
we doing this?" question, Leantime addresses it better than most.
Where it falls short: It's not built for enterprise scale. The
self-hosted version has limitations on governance, and the AI features
are still maturing compared to platforms with deeper investment.
Wekan is a self-hosted Trello alternative. Minimalist boards,
checklists, labels. Free and open-source. If your team only needs
kanban and wants zero overhead, it works.
But it's kanban-only. No AI, no roadmap, no reporting beyond basics. I
included it as a baseline — if your needs are this simple, you don't
need the other six tools on this list.
After six weeks of testing, here's how I'd guide teams:
If you're migrating from Jira Data Center: Look at
ONES.com. Jira-compatible workflows, native AI, on-premise deployment with full feature parity. It solves the specific
problem of "I need to leave Jira but I won't go cloud."
If you're a DevSecOps team: GitLab Ultimate is hard to beat. The
code-to-deployment integration is unmatched.
If you're a small team with strategy focus: Leantime. The goal
cascading is genuinely useful.
If you have Ruby expertise and want full control: Redmine. But
budget for the maintenance burden.
The Atlassian Data Center deadline is real, and 2029 sounds far away
until you realize migrations of this scale take 12-18 months. My
advice: start evaluating now, pick a platform by end of 2026, and
migrate in 2027. Don't be the team scrambling in Q1 2029.
I've spent three decades helping enterprises navigate tool migrations and digital transformations. If you're evaluating self-hosted PM tools or planning a Jira Data Center migration, I'm happy to share more detailed evaluation notes — just reach out in the comments.